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Book Cover
E-book
Author Marchi, Max

Title Analyzing Baseball Data with R, Second Edition
Edition 2nd ed
Published Milton : Chapman and Hall/CRC, 2018

Copies

Description 1 online resource (361 pages)
Series Chapman and Hall/CRC the R Ser
Chapman and Hall/CRC the R Ser
Contents Cover; Half Title; Title Page; Copyright Page; Table of Contents; Preface; Chapter 1: The Baseball Datasets; 1.1 Introduction; 1.2 The Lahman Database: Season-by-Season Data; 1.2.1 Bonds, Aaron, Ruth, and Rodriguez home run trajectories; 1.2.2 Obtaining the database; 1.2.3 The Master table; 1.2.4 The Batting table; 1.2.5 The Pitching table; 1.2.6 The Fielding table; 1.2.7 The Teams table; 1.2.8 Baseball questions; 1.3 Retrosheet Game-by-Game Data; 1.3.1 The 1998 McGwire and Sosa home run race; 1.3.2 Retrosheet; 1.3.3 Game logs; 1.3.4 Obtaining the game logs from Retrosheet
1.3.5 Game log example1.3.6 Baseball questions; 1.4 Retrosheet Play-by-Play Data; 1.4.1 Event files; 1.4.2 Event example; 1.4.3 Baseball questions; 1.5 Pitch-by-Pitch Data; 1.5.1 MLBAM Gameday and PITCHf/x; 1.5.2 PITCHf/x Example; 1.5.3 Baseball questions; 1.6 Player Movement and Off-the-Bat Data; 1.6.1 Statcast; 1.6.2 Baseball Savant data; 1.6.3 Baseball questions; 1.7 Summary; 1.8 Further Reading; 1.9 Exercises; Chapter 2: Introduction to R; 2.1 Introduction; 2.2 Installing R and RStudio; 2.3 The Tidyverse; 2.3.1 dplyr; 2.3.2 The pipe; 2.3.3 ggplot2; 2.3.4 Other packages; 2.4 Data Frames
2.4.1 Career of Warren Spahn2.4.2 Introduction; 2.4.3 Manipulations with data frames; 2.4.4 Merging and selecting from data frames; 2.5 Vectors; 2.5.1 Defining and computing with vectors; 2.5.2 Vector functions; 2.5.3 Vector index and logical variables; 2.6 Objects and Containers in R; 2.6.1 Character data and data frames; 2.6.2 Factors; 2.6.3 Lists; 2.7 Collection of R Commands; 2.7.1 R scripts; 2.7.2 R functions; 2.8 Reading and Writing Data in R; 2.8.1 Importing data from a file; 2.8.2 Saving datasets; 2.9 Packages; 2.10 Splitting, Applying, and Combining Data; 2.10.1 Iterating using map()
2.10.2 Another example2.11 Getting Help; 2.12 Further Reading; 2.13 Exercises; Chapter 3: Graphics; 3.1 Introduction; 3.2 Character Variable; 3.2.1 A bar graph; 3.2.2 Add axes labels and a title; 3.2.3 Other graphs of a character variable; 3.3 Saving Graphs; 3.4 Numeric Variable: One-Dimensional Scatterplot and Histogram; 3.5 Two Numeric Variables; 3.5.1 Scatterplot; 3.5.2 Building a graph, step-by-step; 3.6 A Numeric Variable and a Factor Variable; 3.6.1 Parallel stripcharts; 3.6.2 Parallel boxplots; 3.7 Comparing Ruth, Aaron, Bonds, and A-Rod; 3.7.1 Getting the data
3.7.2 Creating the player data frames3.7.3 Constructing the graph; 3.8 The 1998 Home Run Race; 3.8.1 Getting the data; 3.8.2 Extracting the variables; 3.8.3 Constructing the graph; 3.9 Further Reading; 3.10 Exercises; Chapter 4: The Relation Between Runs and Wins; 4.1 Introduction; 4.2 The Teams Table in the Lahman Database; 4.3 Linear Regression; 4.4 The Pythagorean Formula for Winning Percentage; 4.4.1 The Exponent in the Pythagorean model; 4.4.2 Good and bad predictions by the Pythagorean model; 4.5 How Many Runs for a Win?; 4.6 Further Reading; 4.7 Exercises
Notes Chapter 5: Value of Plays Using Run Expectancy
Print version record
Form Electronic book
Author Albert, Jim
Baumer, Benjamin S
ISBN 9781351107082
1351107089